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Titolo:
Conjunctive representations in learning and memory: Principles of corticaland hippocampal function
Autore:
OReilly, RC; Rudy, JW;
Indirizzi:
Univ Colorado, Dept Psychol, Boulder, CO 80309 USA Univ Colorado Boulder CO USA 80309 o, Dept Psychol, Boulder, CO 80309 USA
Titolo Testata:
PSYCHOLOGICAL REVIEW
fascicolo: 2, volume: 108, anno: 2001,
pagine: 311 - 345
SICI:
0033-295X(200104)108:2<311:CRILAM>2.0.ZU;2-D
Fonte:
ISI
Lingua:
ENG
Soggetto:
TRANSVERSE-PATTERNING PROBLEM; CONFIGURAL ASSOCIATION THEORY; LONG-TERM POTENTIATION; MEDIAL TEMPORAL-LOBE; RECOGNITION MEMORY; DECLARATIVE MEMORY; LATENT INHIBITION; NEURONAL-ACTIVITY; AMNESIC PATIENTS; EPISODIC MEMORY;
Tipo documento:
Review
Natura:
Periodico
Settore Disciplinare:
Social & Behavioral Sciences
Life Sciences
Citazioni:
151
Recensione:
Indirizzi per estratti:
Indirizzo: O'Reilly, RC Univ Colorado, Dept Psychol, 345 UCB, Boulder, CO 80309 USA Univ Colorado 345 UCB Boulder CO USA 80309 lder, CO 80309 USA
Citazione:
R.C. O'Reilly e J.W. Rudy, "Conjunctive representations in learning and memory: Principles of corticaland hippocampal function", PSYCHOL REV, 108(2), 2001, pp. 311-345

Abstract

The authors present a theoretical framework for understanding the roles ofthe hippocampus and neocortex in learning and memory. This framework incorporates a theme found in many theories of hippocampal function: that the hippocampus is responsible for developing conjunctive representations bindingtogether stimulus elements into a unitary representation that can later berecalled from partial input cues. This idea is contradicted by the fact that hippocampally lesioned rats can team nonlinear discrimination problems that require conjunctive representations. The authors' framework accommodates this finding by establishing a principled division of labor, where the cortex is responsible for slow learning that integrates over multiple experiences to extract generalities whereas the hippocampus performs rapid learning of the arbitrary contents of individual experiences. This framework suggests that tasks involving rapid, incidental conjunctive learning are better tests of hippocampal function. The authors implement this framework in a computational neural network model and show that it can account for a wide range of data in animal learning.

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Documento generato il 18/01/20 alle ore 02:13:32